コード例 #1
0
ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestMulNonSquare()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) },
                { R(4), R(5), R(6) }
            });

            SafeMatrix <Rational> b = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(5), R(6), R(7), R(6) },
                { R(6), R(7), R(8), R(9) },
                { R(7), R(8), R(9), R(10) }
            });

            // Act
            SafeMatrix <Rational> actual = a * b;

            // Assert
            SafeMatrix <Rational> expected = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(38), R(44), R(50), R(54) },
                { R(56), R(65), R(74), R(79) },
                { R(74), R(86), R(98), R(104) },
                { R(92), R(107), R(122), R(129) }
            });

            Assert.AreEqual(actual, expected);
        }
コード例 #2
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ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestSetBlock()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) },
                { R(4), R(5), R(6) }
            });

            SafeMatrix <Rational> block = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(0), R(0) },
                { R(0), R(0) }
            });

            // Act
            a.SetBlock(2, 1, block);

            // Assert
            SafeMatrix <Rational> expected = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(0), R(0) },
                { R(4), R(0), R(0) }
            });

            Assert.AreEqual(a, expected);
        }
コード例 #3
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ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestAdd()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) }
            });

            SafeMatrix <Rational> b = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(4), R(5), R(6) },
                { R(5), R(6), R(7) },
                { R(6), R(7), R(8) }
            });

            // Act
            SafeMatrix <Rational> actual = a + b;

            // Assert
            SafeMatrix <Rational> expected = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(5), R(7), R(9) },
                { R(7), R(9), R(11) },
                { R(9), R(11), R(13) }
            });

            Assert.AreEqual(actual, expected);
            Assert.AreEqual(actual - b, a);
        }
コード例 #4
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        /// <summary>
        /// Warning: This method is not thread safe!
        /// </summary>
        public static SafeMatrix SolveLinearSystemFast(SafeMatrix A, SafeMatrix X)
        {
            if (A.RowCount > 35 * 35)
            {
                throw new InvalidOperationException("Not a PSF fitting linear system.");
            }

            if (s_NumVariables != A.ColumnCount)
            {
                LinearSystemFastInitialiseSolution(A.ColumnCount, 35 * 35);
                s_NumVariables = A.ColumnCount;
            }

            double[] a = A.GetElements();
            double[] x = X.GetElements();
            double[] y = new double[A.ColumnCount * X.ColumnCount];

            SolveLinearSystemFast(a, x, A.RowCount, y);

            SafeMatrix rv = new SafeMatrix(X.RowCount, X.ColumnCount);

            rv.SetElements(y);

            return(rv);
        }
コード例 #5
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        public void Calibrate()
        {
            if (m_PixelPos.Count < 3)
            {
                throw new InvalidOperationException("Cannot get a fit from less than 3 points.");
            }

            var A = new SafeMatrix(m_PixelPos.Count, 2);
            var X = new SafeMatrix(m_PixelPos.Count, 1);

            for (int i = 0; i < m_PixelPos.Count; i++)
            {
                A[i, 0] = m_Wavelengths[i];
                A[i, 1] = 1;

                X[i, 0] = m_PixelPos[i];
            }

            SafeMatrix a_T    = A.Transpose();
            SafeMatrix aa     = a_T * A;
            SafeMatrix aa_inv = aa.Inverse();
            SafeMatrix bx     = (aa_inv * a_T) * X;

            m_A = (float)bx[0, 0];
            m_B = (float)bx[1, 0];
        }
コード例 #6
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        protected override void ConfigureObservation(SafeMatrix A, SafeMatrix AReverse, int i)
        {
            A[i, 0] = m_StarPairs[i].x;
            A[i, 1] = m_StarPairs[i].y;
            A[i, 2] = 1;

            AReverse[i, 0] = m_StarPairs[i].ExpectedXTang;
            AReverse[i, 1] = m_StarPairs[i].ExpectedYTang;
            AReverse[i, 2] = 1;
        }
コード例 #7
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        private void CalibrateNonLinearMagModelInternal(List <AbsFluxSpectra> standards)
        {
            m_MagnitudeCoefficients.Clear();
            m_ExtinctionCoefficients.Clear();
            m_SensitivityCoefficients.Clear();
            m_Wavelengths.Clear();

            for (int i = 0; i < standards[0].DeltaMagnitiudes.Count; i++)
            {
                var A = new SafeMatrix(standards.Count, 3);
                var X = new SafeMatrix(standards.Count, 1);

                bool containsNaNs = false;

                // MagAbs = A * MagInst + B * X + C = Km * MagInst + Ke * X + Ks
                for (int j = 0; j < standards.Count; j++)
                {
                    A[j, 0] = -2.5 * Math.Log10(standards[j].ObservedFluxes[i] / standards[j].InputFile.Exposure);
                    A[j, 1] = standards[j].InputFile.AirMass;
                    A[j, 2] = 1;

                    double absMag = -2.5 * Math.Log10(standards[j].AbsoluteFluxes[i]);
                    X[j, 0] = absMag;
                    if (double.IsNaN(absMag) || double.IsNaN(A[j, 0]))
                    {
                        containsNaNs = true;
                    }
                }

                m_Wavelengths.Add(standards[0].ResolvedWavelengths[i]);
                if (!containsNaNs)
                {
                    SafeMatrix a_T    = A.Transpose();
                    SafeMatrix aa     = a_T * A;
                    SafeMatrix aa_inv = aa.Inverse();
                    SafeMatrix bx     = (aa_inv * a_T) * X;

                    float km = (float)bx[0, 0];
                    float ke = (float)bx[1, 0];
                    float ks = (float)bx[2, 0];

                    m_MagnitudeCoefficients.Add(km);
                    m_ExtinctionCoefficients.Add(ke);
                    m_SensitivityCoefficients.Add(ks);
                }
                else
                {
                    m_MagnitudeCoefficients.Add(double.NaN);
                    m_ExtinctionCoefficients.Add(double.NaN);
                    m_SensitivityCoefficients.Add(double.NaN);
                }
            }
        }
コード例 #8
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        private void CalibrateLinearModelInternal(List <AbsFluxSpectra> standards)
        {
            m_MagnitudeCoefficients.Clear();
            m_ExtinctionCoefficients.Clear();
            m_SensitivityCoefficients.Clear();
            m_Wavelengths.Clear();

            for (int i = 0; i < standards[0].DeltaMagnitiudes.Count; i++)
            {
                var A = new SafeMatrix(standards.Count, 2);
                var X = new SafeMatrix(standards.Count, 1);

                bool containsNaNs = false;

                // Delta_Mag = A * X + B = Ke * X + Ks
                for (int j = 0; j < standards.Count; j++)
                {
                    A[j, 0] = standards[j].InputFile.AirMass;
                    A[j, 1] = 1;

                    double deltaMag = standards[j].DeltaMagnitiudes[i];
                    X[j, 0] = deltaMag;
                    if (double.IsNaN(deltaMag))
                    {
                        containsNaNs = true;
                    }
                }

                m_Wavelengths.Add(standards[0].ResolvedWavelengths[i]);
                if (!containsNaNs)
                {
                    SafeMatrix a_T    = A.Transpose();
                    SafeMatrix aa     = a_T * A;
                    SafeMatrix aa_inv = aa.Inverse();
                    SafeMatrix bx     = (aa_inv * a_T) * X;

                    float ke = (float)bx[0, 0];
                    float ks = (float)bx[1, 0];

                    m_MagnitudeCoefficients.Add(1);
                    m_ExtinctionCoefficients.Add(ke);
                    m_SensitivityCoefficients.Add(ks);
                }
                else
                {
                    m_MagnitudeCoefficients.Add(double.NaN);
                    m_ExtinctionCoefficients.Add(double.NaN);
                    m_SensitivityCoefficients.Add(double.NaN);
                }
            }
        }
コード例 #9
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        public static SafeMatrix SolveLinearSystem(SafeMatrix A, SafeMatrix X)
        {
            double[] a = A.GetElements();
            double[] x = X.GetElements();
            double[] y = new double[A.ColumnCount * X.ColumnCount];

            SolveLinearSystem(a, A.RowCount, A.ColumnCount, x, X.RowCount, X.ColumnCount, y);

            SafeMatrix rv = new SafeMatrix(X.RowCount, X.ColumnCount);

            rv.SetElements(y);

            return(rv);
        }
コード例 #10
0
ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestGetBlockShouldFailIndexOutOfBounds()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) },
                { R(4), R(5), R(6) }
            });

            // Act & Assert
            Assert.ThrowsException <IndexOutOfRangeException>(() => a.GetBlock(2, 1, 3, 3));
        }
コード例 #11
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        // Third Order (10 params): Z = A * x * x * x + B * x * x * y + C * y * y * x + D * y * y * y + E * x * x + F * x * y + G * y * y + H * x + I * y + J
        private void SolveThirdOrderFit()
        {
            SafeMatrix A = new SafeMatrix(m_ZValues.Count, 10);
            SafeMatrix X = new SafeMatrix(m_ZValues.Count, 1);

            for (int i = 0; i < m_ZValues.Count; i++)
            {
                A[i, 0] = m_XXXValues[i];
                A[i, 1] = m_XXYValues[i];
                A[i, 2] = m_XYYValues[i];
                A[i, 3] = m_YYYValues[i];
                A[i, 4] = m_XXValues[i];
                A[i, 5] = m_XYValues[i];
                A[i, 6] = m_YYValues[i];
                A[i, 7] = m_XValues[i];
                A[i, 8] = m_YValues[i];
                A[i, 9] = 1;

                X[i, 0] = m_ZValues[i];
            }

            SafeMatrix a_T    = A.Transpose();
            SafeMatrix aa     = a_T * A;
            SafeMatrix aa_inv = aa.Inverse();
            SafeMatrix bx     = (aa_inv * a_T) * X;

            m_ThirdA = bx[0, 0];
            m_ThirdB = bx[1, 0];
            m_ThirdC = bx[2, 0];
            m_ThirdD = bx[3, 0];
            m_ThirdE = bx[4, 0];
            m_ThirdF = bx[5, 0];
            m_ThirdG = bx[6, 0];
            m_ThirdH = bx[7, 0];
            m_ThirdI = bx[8, 0];
            m_ThirdJ = bx[9, 0];

            m_Residuals.Clear();

            double sumResidualsSQ = 0;

            for (int i = 0; i < m_ZValues.Count; i++)
            {
                double res = m_ZValues[i] - ComputeThirdOrderValue(m_XValues[i], m_YValues[i]);
                m_Residuals.Add(res);
                sumResidualsSQ += res * res;
            }

            m_ThirdVariance = Math.Sqrt(sumResidualsSQ / (m_ZValues.Count - 1));
        }
コード例 #12
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        protected override void ReadSolvedReversedConstants(SafeMatrix bx, SafeMatrix by)
        {
            Const_A1 = bx[0, 0];
            Const_B1 = bx[1, 0];
            Const_C1 = bx[2, 0];
            Const_D1 = bx[3, 0];
            Const_E1 = bx[4, 0];
            Const_F1 = bx[5, 0];

            Const_G1 = by[0, 0];
            Const_H1 = by[1, 0];
            Const_K1 = by[2, 0];
            Const_L1 = by[3, 0];
            Const_M1 = by[4, 0];
            Const_N1 = by[5, 0];
        }
コード例 #13
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        protected override bool ReadSolvedConstants(SafeMatrix bx, SafeMatrix by)
        {
            Const_A = bx[0, 0];
            Const_B = bx[1, 0];
            Const_C = bx[2, 0];
            Const_D = bx[3, 0];
            Const_E = bx[4, 0];
            Const_F = bx[5, 0];

            Const_G = by[0, 0];
            Const_H = by[1, 0];
            Const_K = by[2, 0];
            Const_L = by[3, 0];
            Const_M = by[4, 0];
            Const_N = by[5, 0];

            return(true);
        }
コード例 #14
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ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestMulShouldFailIncompatibleDimensions()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) }
            });

            SafeMatrix <Rational> b = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(5), R(6), R(7), R(6) },
                { R(6), R(7), R(8), R(9) }
            });

            // Act & Assert
            Assert.ThrowsException <ArgumentException>(() => a * b);
        }
コード例 #15
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ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestSubShouldFailDifferentDimensions()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) }
            });

            SafeMatrix <Rational> b = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(4), R(5), R(6) },
                { R(5), R(6), R(7) }
            });

            // Act & Assert
            Assert.ThrowsException <ArgumentException>(() => a - b);
        }
コード例 #16
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        protected override bool ReadSolvedConstants(SafeMatrix bx, SafeMatrix by)
        {
            Const_A = bx[0, 0];
            Const_B = bx[1, 0];
            Const_C = bx[2, 0];

            Const_D = by[0, 0];
            Const_E = by[1, 0];
            Const_F = by[2, 0];

            Const_A1 = Const_E / (Const_E * Const_A - Const_B * Const_D);
            Const_B1 = -Const_B / (Const_E * Const_A - Const_B * Const_D);
            Const_C1 = (Const_B * Const_F - Const_C * Const_E) / (Const_E * Const_A - Const_B * Const_D);
            Const_D1 = Const_D / (Const_B * Const_D - Const_A * Const_E);
            Const_E1 = -Const_A / (Const_B * Const_D - Const_A * Const_E);
            Const_F1 = (Const_A * Const_F - Const_C * Const_D) / (Const_B * Const_D - Const_A * Const_E);

            return(false);
        }
コード例 #17
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ファイル: Main.cs プロジェクト: r-c-s/linalg
    private static void SafeMatrixDemo()
    {
        Console.WriteLine("-------MATRIX OF COMPLEX NUMBERS DEMO-------");
        SafeMatrix <Complex> A = Utils.RandomMatrix(3, 3, Utils.RandomComplex);
        SafeMatrix <Complex> B = Utils.RandomMatrix(3, 3, Utils.RandomComplex);

        Console.WriteLine("A:");
        Console.WriteLine(A);
        Console.WriteLine();
        Console.WriteLine("B:");
        Console.WriteLine(B);
        Console.WriteLine();

        Console.WriteLine("A + B:");
        Console.WriteLine(A + B);
        Console.WriteLine();

        Console.WriteLine("A - B:");
        Console.WriteLine(A - B);
        Console.WriteLine();

        Console.WriteLine("A * B:");
        Console.WriteLine(A * B);
        Console.WriteLine();

        Complex scalar = Utils.RandomComplex(9, 9);

        Console.WriteLine($"A * {scalar}:");
        Console.WriteLine(A * scalar);
        Console.WriteLine();
        Console.WriteLine($"B * {scalar}:");
        Console.WriteLine(B * scalar);
        Console.WriteLine();

        Console.WriteLine("A transpose:");
        Console.WriteLine(A.Transpose());
        Console.WriteLine();
        Console.WriteLine("B transpose:");
        Console.WriteLine(B.Transpose());
        Console.WriteLine();
    }
コード例 #18
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ファイル: MatrixTests.cs プロジェクト: r-c-s/linalg
        public void TestGetBlock()
        {
            // Arrange
            SafeMatrix <Rational> a = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(1), R(2), R(3) },
                { R(2), R(3), R(4) },
                { R(3), R(4), R(5) },
                { R(4), R(5), R(6) }
            });

            // Act
            SafeMatrix <Rational> actual = a.GetBlock(2, 1, 2, 2);

            // Assert
            SafeMatrix <Rational> expected = new SafeMatrix <Rational>(
                new Rational[, ] {
                { R(4), R(5) },
                { R(5), R(6) }
            });

            Assert.AreEqual(actual, expected);
        }
コード例 #19
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        // First Order (3 params): Z = A * x + B * y + C
        private void SolveFirstOrderFit()
        {
            SafeMatrix A = new SafeMatrix(m_ZValues.Count, 3);
            SafeMatrix X = new SafeMatrix(m_ZValues.Count, 1);

            for (int i = 0; i < m_ZValues.Count; i++)
            {
                A[i, 0] = m_XValues[i];
                A[i, 1] = m_YValues[i];
                A[i, 2] = 1;

                X[i, 0] = m_ZValues[i];
            }

            SafeMatrix a_T    = A.Transpose();
            SafeMatrix aa     = a_T * A;
            SafeMatrix aa_inv = aa.Inverse();
            SafeMatrix bx     = (aa_inv * a_T) * X;

            m_FirstA = bx[0, 0];
            m_FirstB = bx[1, 0];
            m_FirstC = bx[2, 0];

            m_Residuals.Clear();

            double sumResidualsSQ = 0;

            for (int i = 0; i < m_ZValues.Count; i++)
            {
                double res = m_ZValues[i] - ComputeFirstOrderValue(m_XValues[i], m_YValues[i]);
                m_Residuals.Add(res);
                sumResidualsSQ += res * res;
            }

            m_FirstVariance = Math.Sqrt(sumResidualsSQ / (m_ZValues.Count - 1));
        }
コード例 #20
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        internal void GenerateBackgroundModelParameters(int order, double depth)
        {
            Random rnd = new Random((int)DateTime.Now.Ticks);

            if (order == 1)
            {
                // z = ax + by + c

                int dist = rnd.Next(m_X0, m_X0 + (int)(1.2 * m_Radius));
                int d2   = rnd.Next((int)depth / 2, (int)depth);

                SafeMatrix A = new SafeMatrix(3, 3);
                SafeMatrix X = new SafeMatrix(3, 1);

                A[0, 0] = m_X0; A[0, 1] = m_Y0; A[0, 2] = 1; X[0, 0] = depth;
                A[1, 0] = m_X0 + dist / 2; A[1, 1] = m_Y0 + dist / 3; A[1, 2] = 1; X[1, 0] = d2;
                A[2, 0] = m_X0 + dist; A[2, 1] = m_Y0 + dist / 2; A[2, 2] = 1; X[2, 0] = 0;

                SafeMatrix a_T    = A.Transpose();
                SafeMatrix aa     = a_T * A;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                this.A = bx[0, 0];
                B      = bx[1, 0];
                C      = bx[2, 0];
            }
            else if (order == 2)
            {
                // z = axx + bxy + cyy + dx + ey + f

                int[]    xArr = new int[6];
                int[]    yArr = new int[6];
                double[] zArr = new double[6];

                xArr[0] = m_X0; yArr[0] = m_Y0; zArr[0] = depth;
                xArr[1] = m_X0 + m_Radius; yArr[1] = m_Y0 + m_Radius / 3; zArr[1] = 0;
                for (int i = 2; i < 6; i++)
                {
                    xArr[i] = rnd.Next(m_X0, m_X0 + (int)(1.2 * m_Radius));
                    yArr[i] = rnd.Next(m_Y0, m_Y0 + (int)(0.6 * m_Radius));
                    zArr[i] = rnd.Next(0, (int)depth);
                }

                // Start with an approximation
                // z = axx +     + cyy +         + f

                SafeMatrix A = new SafeMatrix(3, 3);
                SafeMatrix X = new SafeMatrix(3, 1);

                for (int i = 0; i < 3; i++)
                {
                    A[i, 0] = xArr[i] * xArr[i];
                    A[i, 1] = yArr[i] * yArr[i];
                    A[i, 2] = 1;
                    X[i, 0] = zArr[i];
                }

                SafeMatrix a_T    = A.Transpose();
                SafeMatrix aa     = a_T * A;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                this.A = bx[0, 0];
                C      = bx[1, 0];
                F      = bx[2, 0];

                B = 0;
                D = 0;
                E = 0;

                /*
                 * A = new SafeMatrix(6, 6);
                 * X = new SafeMatrix(6, 1);
                 *
                 * for (int i = 0; i < 6; i++)
                 * {
                 *      A[i, 0] = xArr[i] * xArr[i];
                 *      A[i, 1] = xArr[i] * yArr[i];
                 *      A[i, 2] = yArr[i] * yArr[i];
                 *      A[i, 3] = xArr[i];
                 *      A[i, 4] = yArr[i];
                 *      A[i, 5] = 1;
                 *      X[i, 0] = zArr[i];
                 * }
                 *
                 * a_T = A.Transpose();
                 * aa = a_T * A;
                 * aa_inv = aa.Inverse();
                 * bx = (aa_inv * a_T) * X;
                 *
                 * m_A = bx[0, 0];
                 * m_B = bx[1, 0];
                 * m_C = bx[2, 0];
                 * m_D = bx[3, 0];
                 * m_E = bx[4, 0];
                 * m_F = bx[5, 0];
                 */
            }
            else if (order == 3)
            {
                // z = axxx + bxxy + cxyy + dyyy + exx + fxy + gyy + hx + iy + j

                int[]    xArr = new int[10];
                int[]    yArr = new int[10];
                double[] zArr = new double[10];

                xArr[0] = m_X0; yArr[0] = m_Y0; zArr[0] = depth;
                xArr[1] = m_X0 + m_Radius; yArr[1] = m_Y0 + m_Radius / 3; zArr[1] = 0;
                for (int i = 2; i < 6; i++)
                {
                    xArr[i] = rnd.Next(m_X0, m_X0 + (int)(1.2 * m_Radius));
                    yArr[i] = rnd.Next(m_Y0, m_Y0 + (int)(0.6 * m_Radius));
                    zArr[i] = rnd.Next(0, (int)depth);
                }

                // Start with an approximation
                // z = axxx +     + dyyy +   +  fxy +    + j

                SafeMatrix A = new SafeMatrix(4, 4);
                SafeMatrix X = new SafeMatrix(4, 1);

                for (int i = 0; i < 4; i++)
                {
                    A[i, 0] = xArr[i] * xArr[i] * xArr[i];
                    A[i, 1] = yArr[i] * yArr[i] * yArr[i];
                    A[i, 2] = xArr[i] * yArr[i];
                    A[i, 3] = 1;
                    X[i, 0] = zArr[i];
                }

                SafeMatrix a_T    = A.Transpose();
                SafeMatrix aa     = a_T * A;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                this.A = bx[0, 0];
                D      = bx[1, 0];
                F      = bx[2, 0];
                J      = bx[3, 0];

                B = 0;
                C = 0;
                E = 0;
                G = 0;
                H = 0;
                I = 0;
            }
        }
コード例 #21
0
        private void CalculateGagnitudeFit(Dictionary <IStar, double> measurements, double fixedColourCoeff)
        {
            List <MagFitEntry> datapoints = new List <MagFitEntry>();

            foreach (IStar star in measurements.Keys)
            {
                UCAC4Entry ucac4 = (UCAC4Entry)star;
                if (!double.IsNaN(ucac4.Mag_r) && Math.Abs(ucac4.Mag_r) > 0.00001 && !double.IsNaN(ucac4.MagB) && !double.IsNaN(ucac4.MagV))
                {
                    datapoints.Add(new MagFitEntry()
                    {
                        APASS_Sloan_r        = ucac4.Mag_r,
                        APASS_BV_Colour      = ucac4.MagB - ucac4.MagV,
                        MedianIntensity      = measurements[star],
                        MedianIntensityError = 0.05 * measurements[star]
                    });
                }
            }

            float FIXED_COLOUR_COEFF = (float)fixedColourCoeff;

            for (int i = 0; i < datapoints.Count; i++)
            {
                datapoints[i].InstrMag    = -2.5 * Math.Log10(datapoints[i].MedianIntensity) + 32 - datapoints[i].APASS_BV_Colour * FIXED_COLOUR_COEFF;
                datapoints[i].InstrMagErr = Math.Abs(-2.5 * Math.Log10((datapoints[i].MedianIntensity + datapoints[i].MedianIntensityError) / datapoints[i].MedianIntensity));
            }

            datapoints = datapoints.Where(x => !double.IsNaN(x.InstrMag) && x.InstrMagErr < 0.2).ToList();

            if (datapoints.Count < 4)
            {
                return;
            }

            double variance = 0;
            double Ka       = 0;
            double Kb       = 0;

            int MAX_ITTER = 2;

            for (int itt = 0; itt <= MAX_ITTER; itt++)
            {
                SafeMatrix A = new SafeMatrix(datapoints.Count, 2);
                SafeMatrix X = new SafeMatrix(datapoints.Count, 1);

                int idx = 0;
                for (int i = 0; i < datapoints.Count; i++)
                {
                    A[idx, 0] = datapoints[i].InstrMag;
                    A[idx, 1] = 1;

                    X[idx, 0] = datapoints[i].APASS_Sloan_r;

                    idx++;
                }

                SafeMatrix a_T    = A.Transpose();
                SafeMatrix aa     = a_T * A;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                Ka = bx[0, 0];
                Kb = bx[1, 0];

                double resSum = 0;
                for (int i = 0; i < datapoints.Count; i++)
                {
                    double computedMag = Ka * datapoints[i].InstrMag + Kb;

                    double diff = computedMag - datapoints[i].APASS_Sloan_r;

                    resSum += diff * diff;
                    datapoints[i].Residual = diff;
                }

                variance = Math.Sqrt(resSum / datapoints.Count);

                if (itt < MAX_ITTER)
                {
                    datapoints.RemoveAll(x => Math.Abs(x.Residual) > 2 * variance || Math.Abs(x.Residual) > 0.2);
                }
            }

            Trace.WriteLine(string.Format("r' + {3} * (B-V) +  = {0} * M + {1} +/- {2}", Ka.ToString("0.0000"), Kb.ToString("0.0000"), variance.ToString("0.00"), FIXED_COLOUR_COEFF.ToString("0.00000")));
        }
コード例 #22
0
 protected abstract void ConfigureObservation(SafeMatrix A, SafeMatrix AReverse, int i);
コード例 #23
0
        private bool LeastSquareSolve(double ra0Deg, double de0Deg, int minNumberOfStars)
        {
            int[] NUM_CONSTANTS = new int[] { 3, 6, 10 };

            SafeMatrix A = new SafeMatrix(m_StarPairs.Count, NUM_CONSTANTS[(int)m_FitOrder]);
            SafeMatrix X = new SafeMatrix(m_StarPairs.Count, 1);
            SafeMatrix Y = new SafeMatrix(m_StarPairs.Count, 1);

            SafeMatrix AReverse = new SafeMatrix(m_StarPairs.Count, NUM_CONSTANTS[(int)m_FitOrder]);
            SafeMatrix XReverse = new SafeMatrix(m_StarPairs.Count, 1);
            SafeMatrix YReverse = new SafeMatrix(m_StarPairs.Count, 1);

            int numStars = 0;

            for (int i = 0; i < m_StarPairs.Count; i++)
            {
                m_StarPairs[i].FitInfo.UsedInSolution = false;

                if (m_StarPairs[i].FitInfo.ExcludedForHighResidual)
                {
                    continue;
                }

                numStars++;
                m_StarPairs[i].FitInfo.UsedInSolution = true;

                ConfigureObservation(A, AReverse, i);

                X[i, 0]        = m_StarPairs[i].ExpectedXTang;
                Y[i, 0]        = m_StarPairs[i].ExpectedYTang;
                XReverse[i, 0] = m_StarPairs[i].x;
                YReverse[i, 0] = m_StarPairs[i].y;
            }

            // Insufficient stars to solve the plate
            if (numStars < minNumberOfStars)
            {
                if (TangraConfig.Settings.TraceLevels.PlateSolving.TraceVerbose())
                {
                    Debug.WriteLine(string.Format("Insufficient number of stars to do a fit. At least {0} stars requested.", minNumberOfStars));
                }

                return(false);
            }

            SafeMatrix a_T    = A.Transpose();
            SafeMatrix aa     = a_T * A;
            SafeMatrix aa_inv = aa.Inverse();
            SafeMatrix bx     = (aa_inv * a_T) * X;
            SafeMatrix by     = (aa_inv * a_T) * Y;

            if (ReadSolvedConstants(bx, by))
            {
                a_T    = AReverse.Transpose();
                aa     = a_T * AReverse;
                aa_inv = aa.Inverse();
                bx     = (aa_inv * a_T) * XReverse;
                by     = (aa_inv * a_T) * YReverse;

                ReadSolvedReversedConstants(bx, by);
            }

            double residualSum         = 0;
            double residualSumArcSecRA = 0;
            double residualSumArcSecDE = 0;
            int    numResiduals        = 0;

            var absResRAArcSec = new List <double>();
            var absResDEArcSec = new List <double>();

            for (int i = 0; i < m_StarPairs.Count; i++)
            {
                double computedXTang, computedYTang;
                GetTangentCoordsFromImageCoords(m_StarPairs[i].x, m_StarPairs[i].y, out computedXTang, out computedYTang);

                m_StarPairs[i].FitInfo.ResidualXTang = m_StarPairs[i].ExpectedXTang - computedXTang;
                m_StarPairs[i].FitInfo.ResidualYTang = m_StarPairs[i].ExpectedYTang - computedYTang;

                double raComp, deComp;
                TangentPlane.TangentToCelestial(computedXTang, computedYTang, ra0Deg, de0Deg, out raComp, out deComp);

                m_StarPairs[i].FitInfo.ResidualRAArcSec = 3600.0 * AngleUtility.Elongation(m_StarPairs[i].RADeg, 0, raComp, 0);
                m_StarPairs[i].FitInfo.ResidualDEArcSec = 3600.0 * AngleUtility.Elongation(0, m_StarPairs[i].DEDeg, 0, deComp);

                if (!m_StarPairs[i].FitInfo.UsedInSolution)
                {
                    continue;
                }
                numResiduals++;
                residualSum         += Math.Abs(m_StarPairs[i].FitInfo.ResidualXTang * m_StarPairs[i].FitInfo.ResidualYTang);
                residualSumArcSecRA += m_StarPairs[i].FitInfo.ResidualRAArcSec * m_StarPairs[i].FitInfo.ResidualRAArcSec;
                residualSumArcSecDE += m_StarPairs[i].FitInfo.ResidualDEArcSec * m_StarPairs[i].FitInfo.ResidualDEArcSec;
                absResRAArcSec.Add(Math.Abs(m_StarPairs[i].FitInfo.ResidualRAArcSec));
                absResDEArcSec.Add(Math.Abs(m_StarPairs[i].FitInfo.ResidualDEArcSec));
            }

            Variance         = residualSum / (numResiduals - 1);
            VarianceArcSecRA = residualSumArcSecRA / (numResiduals - 1);
            VarianceArcSecDE = residualSumArcSecDE / (numResiduals - 1);

            // Uncertainty based on Astrometrica's formula of median residual devided by SQRT(num stars)
            UncertaintyArcSecRA = absResRAArcSec.Median() / Math.Sqrt(numResiduals);
            UncertaintyArcSecDE = absResDEArcSec.Median() / Math.Sqrt(numResiduals);


            return(true);
        }
コード例 #24
0
 protected abstract void ReadSolvedReversedConstants(SafeMatrix bx, SafeMatrix by);
コード例 #25
0
        private void RecalculateFit()
        {
            int totalMeasuredFrames = m_Exports.SelectMany(x => x.Entries).Select(x => x.MeasuredFrames).ToList().Median();

            List <TangraExportEntry> datapoints = m_Exports
                                                  .SelectMany(x => x.Entries)
                                                  .Where(x =>
                                                         !float.IsNaN(x.APASS_Sloan_r) && Math.Abs(x.APASS_Sloan_r) > 0.00001 && !float.IsNaN(x.MedianIntensity) &&
                                                         !float.IsNaN(x.MedianIntensity) && !float.IsNaN(x.APASS_BV_Colour) && x.MeasuredFrames > 0.95 * totalMeasuredFrames && x.SaturatedFrames == 0)
                                                  .ToList();

            for (int i = 0; i < datapoints.Count; i++)
            {
                datapoints[i].InstrMag    = -2.5 * Math.Log10(datapoints[i].MedianIntensity) + 32;
                datapoints[i].InstrMagErr = Math.Abs(-2.5 * Math.Log10((datapoints[i].MedianIntensity + datapoints[i].MedianIntensityError) / datapoints[i].MedianIntensity));
            }

            datapoints = datapoints.Where(x => x.InstrMagErr < 0.2).ToList();

            if (datapoints.Count < 4)
            {
                return;
            }

            double variance = 0;
            double Ka       = 0;
            double Kb       = 0;
            double Kc       = 0;

            int MAX_ITTER = 2;

            for (int itt = 0; itt <= MAX_ITTER; itt++)
            {
                SafeMatrix A = new SafeMatrix(datapoints.Count, 3);
                SafeMatrix X = new SafeMatrix(datapoints.Count, 1);

                int idx = 0;
                for (int i = 0; i < datapoints.Count; i++)
                {
                    A[idx, 0] = datapoints[i].InstrMag;
                    A[idx, 1] = datapoints[i].APASS_BV_Colour;
                    A[idx, 2] = 1;

                    X[idx, 0] = datapoints[i].APASS_Sloan_r;

                    idx++;
                }

                SafeMatrix a_T    = A.Transpose();
                SafeMatrix aa     = a_T * A;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                Ka = bx[0, 0];
                Kb = bx[1, 0];
                Kc = bx[2, 0];

                double resSum = 0;
                for (int i = 0; i < datapoints.Count; i++)
                {
                    double computedMag = Ka * datapoints[i].InstrMag + Kb * datapoints[i].APASS_BV_Colour + Kc;

                    double diff = computedMag - datapoints[i].APASS_Sloan_r;

                    resSum += diff * diff;
                    datapoints[i].Residual = diff;
                }

                variance = Math.Sqrt(resSum / datapoints.Count);

                if (itt < MAX_ITTER)
                {
                    datapoints.RemoveAll(x => Math.Abs(x.Residual) > 2 * variance || Math.Abs(x.Residual) > 0.2);
                }
            }

            Trace.WriteLine(string.Format("r' = {0} * M + {1} * (B-V) + {2} +/- {3}", Ka.ToString("0.0000"), Kb.ToString("0.0000"), Kc.ToString("0.00"), variance.ToString("0.00")));

            if (miColourPlot.Checked)
            {
                PlotColourFitData(datapoints, Ka, Kb, Kc, variance);
            }
        }
コード例 #26
0
        public FocalLengthFit ComputeFocalLengthFit()
        {
            if (m_FocalLengthFit != null)
            {
                return(m_FocalLengthFit);
            }

            List <DistSolveEntry> entries = new List <DistSolveEntry>();

            for (int i = 0; i < m_Pairs.Count; i++)
            {
                if (!m_Pairs[i].FitInfo.UsedInSolution)
                {
                    continue;
                }
                if (m_Pairs[i].FitInfo.ExcludedForHighResidual)
                {
                    continue;
                }

                for (int j = 0; j < m_Pairs.Count; j++)
                {
                    if (i == j)
                    {
                        continue;
                    }
                    if (!m_Pairs[j].FitInfo.UsedInSolution)
                    {
                        continue;
                    }
                    if (m_Pairs[j].FitInfo.ExcludedForHighResidual)
                    {
                        continue;
                    }

                    DistSolveEntry entry = new DistSolveEntry();
                    entry.DX = Math.Abs(m_Pairs[i].x - m_Pairs[j].x);
                    entry.DY = Math.Abs(m_Pairs[i].y - m_Pairs[j].y);

                    entry.StarNo1 = m_Pairs[i].StarNo;
                    entry.StarNo2 = m_Pairs[j].StarNo;

                    // NOTE: two ways of computing distances - by vx,vy,vz and Elongation()
                    //entry.DistRadians = Math.Acos(m_Pairs[i].VX * m_Pairs[j].VX + m_Pairs[i].VY * m_Pairs[j].VY + m_Pairs[i].VZ * m_Pairs[j].VZ);

                    double elong = AngleUtility.Elongation(m_Pairs[i].RADeg, m_Pairs[i].DEDeg, m_Pairs[j].RADeg, m_Pairs[j].DEDeg);
                    entry.DistRadians = elong * Math.PI / 180.0;

                    if (entry.DX == 0 || entry.DY == 0)
                    {
                        continue;
                    }

                    entries.Add(entry);
                }
            }

            SafeMatrix A = new SafeMatrix(entries.Count, 2);
            SafeMatrix X = new SafeMatrix(entries.Count, 1);

            int numStars = 0;

            foreach (DistSolveEntry entry in entries)
            {
                A[numStars, 0] = entry.DX * entry.DX;
                A[numStars, 1] = entry.DY * entry.DY;

                X[numStars, 0] = entry.DistRadians * entry.DistRadians;

                numStars++;
            }

            // Insufficient stars to solve the plate
            if (numStars < 3)
            {
                return(null);
            }

            SafeMatrix a_T    = A.Transpose();
            SafeMatrix aa     = a_T * A;
            SafeMatrix aa_inv = aa.Inverse();
            SafeMatrix bx     = (aa_inv * a_T) * X;

            double a = bx[0, 0];
            double b = bx[1, 0];

            double residualSum  = 0;
            int    numResiduals = 0;

            foreach (DistSolveEntry entry in entries)
            {
                entry.ResidualRadians = entry.DistRadians - Math.Sqrt(a * entry.DX * entry.DX + b * entry.DY * entry.DY);
                entry.ResidualPercent = entry.ResidualRadians * 100.0 / entry.DistRadians;
                entry.ResidualArcSec  = 3600.0 * entry.ResidualRadians * 180.0 / Math.PI;

                numResiduals++;
                residualSum += entry.ResidualRadians * entry.ResidualRadians;
            }

            double variance = Math.Sqrt(residualSum / (numResiduals - 1));

            return(new FocalLengthFit(a, b, variance, entries));
        }
コード例 #27
0
        public static StarMagnitudeFit PerformFit(
            IAstrometryController astrometryController,
            IVideoController videoController,
            int bitPix,
            uint maxSignalValue,
            FitInfo astrometricFit,
            TangraConfig.PhotometryReductionMethod photometryReductionMethod,
            TangraConfig.PsfQuadrature psfQuadrature,
            TangraConfig.PsfFittingMethod psfFittingMethod,
            TangraConfig.BackgroundMethod photometryBackgroundMethod,
            TangraConfig.PreProcessingFilter filter,
            List <IStar> catalogueStars,
            Guid magnitudeBandId,
            float encodingGamma,
            TangraConfig.KnownCameraResponse reverseCameraResponse,
            float?aperture,
            float?annulusInnerRadius,
            int?annulusMinPixels,
            ref float empericalPSFR0)
        {
            uint saturatedValue = TangraConfig.Settings.Photometry.Saturation.GetSaturationForBpp(bitPix, maxSignalValue);

            MeasurementsHelper measurer = new MeasurementsHelper(
                bitPix,
                photometryBackgroundMethod,
                TangraConfig.Settings.Photometry.SubPixelSquareSize,
                saturatedValue);

            measurer.SetCoreProperties(
                annulusInnerRadius ?? TangraConfig.Settings.Photometry.AnnulusInnerRadius,
                annulusMinPixels ?? TangraConfig.Settings.Photometry.AnnulusMinPixels,
                CorePhotometrySettings.Default.RejectionBackgroundPixelsStdDev,
                2 /* TODO: This must be configurable */);

            var bgProvider = new BackgroundProvider(videoController);

            measurer.GetImagePixelsCallback += new MeasurementsHelper.GetImagePixelsDelegate(bgProvider.measurer_GetImagePixelsCallback);

            List <double> intencities    = new List <double>();
            List <double> magnitudes     = new List <double>();
            List <double> colours        = new List <double>();
            List <double> residuals      = new List <double>();
            List <bool>   saturatedFlags = new List <bool>();
            List <IStar>  stars          = new List <IStar>();
            List <PSFFit> gaussians      = new List <PSFFit>();

            List <MagFitRecord> fitRecords = new List <MagFitRecord>();

            AstroImage currentAstroImage = videoController.GetCurrentAstroImage(false);
            Rectangle  osdRectToExclude  = astrometryController.OSDRectToExclude;
            Rectangle  rectToInclude     = astrometryController.RectToInclude;
            bool       limitByInclusion  = astrometryController.LimitByInclusion;

            int matSize = CorePhotometrySettings.Default.MatrixSizeForCalibratedPhotometry;

            double a             = double.NaN;
            double b             = double.NaN;
            double c             = double.NaN;
            int    excludedStars = 0;
            double empericalFWHM = double.NaN;

            try
            {
                foreach (PlateConstStarPair pair in astrometricFit.AllStarPairs)
                {
                    if (limitByInclusion && !rectToInclude.Contains((int)pair.x, (int)pair.y))
                    {
                        continue;
                    }
                    if (!limitByInclusion && osdRectToExclude.Contains((int)pair.x, (int)pair.y))
                    {
                        continue;
                    }

                    IStar star = catalogueStars.Find(s => s.StarNo == pair.StarNo);
                    if (star == null || double.IsNaN(star.Mag) || star.Mag == 0)
                    {
                        continue;
                    }

                    uint[,] data = currentAstroImage.GetMeasurableAreaPixels((int)pair.x, (int)pair.y, matSize);

                    PSFFit fit = new PSFFit((int)pair.x, (int)pair.y);
                    fit.Fit(data, PSF_FIT_AREA_SIZE);
                    if (!fit.IsSolved)
                    {
                        continue;
                    }

                    MagFitRecord record = new MagFitRecord();
                    record.Star       = star;
                    record.Pair       = pair;
                    record.PsfFit     = fit;
                    record.Saturation = IsSaturated(data, matSize, saturatedValue);

                    if (!EXCLUDE_SATURATED_STARS || !record.Saturation)
                    {
                        fitRecords.Add(record);
                    }
                }

                // We need the average R0 if it hasn't been determined yet
                if (float.IsNaN(empericalPSFR0))
                {
                    empericalPSFR0 = 0;
                    foreach (MagFitRecord rec in fitRecords)
                    {
                        empericalPSFR0 += (float)rec.PsfFit.R0;
                    }
                    empericalPSFR0 /= fitRecords.Count;
                }

                empericalFWHM = 2 * Math.Sqrt(Math.Log(2)) * empericalPSFR0;

                foreach (MagFitRecord record in fitRecords)
                {
                    ImagePixel center   = new ImagePixel(255, record.Pair.x, record.Pair.y);
                    int        areaSize = filter == TangraConfig.PreProcessingFilter.NoFilter ? 17 : 19;

                    int centerX = (int)Math.Round(center.XDouble);
                    int centerY = (int)Math.Round(center.YDouble);

                    uint[,] data             = currentAstroImage.GetMeasurableAreaPixels(centerX, centerY, areaSize);
                    uint[,] backgroundPixels = currentAstroImage.GetMeasurableAreaPixels(centerX, centerY, 35);

                    measurer.MeasureObject(
                        center,
                        data,
                        backgroundPixels,
                        currentAstroImage.Pixelmap.BitPixCamera,
                        filter,
                        photometryReductionMethod,
                        psfQuadrature,
                        psfFittingMethod,
                        aperture != null ? aperture.Value : (float)Aperture(record.PsfFit.FWHM),
                        record.PsfFit.FWHM,
                        (float)empericalFWHM,
                        new FakeIMeasuredObject(record.PsfFit),
                        null,
                        null,
                        false);

                    double intensity = measurer.TotalReading - measurer.TotalBackground;
                    if (intensity > 0)
                    {
                        var mag = record.Star.GetMagnitudeForBand(magnitudeBandId);
                        var clr = record.Star.MagJ - record.Star.MagK;

                        if (!double.IsNaN(mag) && !double.IsNaN(clr) && !double.IsInfinity(mag) && !double.IsInfinity(clr))
                        {
                            intencities.Add(intensity);
                            magnitudes.Add(record.Star.GetMagnitudeForBand(magnitudeBandId));
                            colours.Add(record.Star.MagJ - record.Star.MagK);

                            gaussians.Add(record.PsfFit);
                            stars.Add(record.Star);
                            saturatedFlags.Add(measurer.HasSaturatedPixels || record.PsfFit.IMax >= measurer.SaturationValue);
                        }
                    }
                }


                // Remove stars with unusual PSF fit radii (once only)
                double sum = 0;
                for (int i = 0; i < gaussians.Count; i++)
                {
                    sum += gaussians[i].R0;
                }
                double averageR = sum / gaussians.Count;

                residuals.Clear();
                sum = 0;
                for (int i = 0; i < gaussians.Count; i++)
                {
                    residuals.Add(averageR - gaussians[i].R0);
                    sum += (averageR - gaussians[i].R0) * (averageR - gaussians[i].R0);
                }
                double stdDev = Math.Sqrt(sum) / gaussians.Count;

                if (EXCLUDE_BAD_RESIDUALS)
                {
                    for (int i = residuals.Count - 1; i >= 0; i--)
                    {
                        if (Math.Abs(residuals[i]) > 6 * stdDev)
                        {
                            intencities.RemoveAt(i);
                            magnitudes.RemoveAt(i);
                            colours.RemoveAt(i);
                            stars.RemoveAt(i);
                            gaussians.RemoveAt(i);
                            saturatedFlags.RemoveAt(i);
                        }
                    }
                }

                double maxResidual = Math.Max(0.1, TangraConfig.Settings.Photometry.MaxResidualStellarMags);

                for (int itter = 1; itter <= MAX_ITERR; itter++)
                {
                    residuals.Clear();

                    SafeMatrix A = new SafeMatrix(intencities.Count, 3);
                    SafeMatrix X = new SafeMatrix(intencities.Count, 1);

                    int idx = 0;
                    for (int i = 0; i < intencities.Count; i++)
                    {
                        A[idx, 0] = magnitudes[i];
                        A[idx, 1] = colours[i];
                        A[idx, 2] = 1;

                        X[idx, 0] = -2.5 * Math.Log10(intencities[i]);

                        idx++;
                    }

                    SafeMatrix a_T    = A.Transpose();
                    SafeMatrix aa     = a_T * A;
                    SafeMatrix aa_inv = aa.Inverse();
                    SafeMatrix bx     = (aa_inv * a_T) * X;

                    double Ka = bx[0, 0];
                    double Kb = bx[1, 0];
                    double Kc = bx[2, 0];

                    // -2.5 * a * Log(Median-Intensity) = A * Mv + B * Mjk + C - b
                    // -2.5 * Log(Median-Intensity) = Ka * Mv + Kb * Mjk + Kc
                    // Mv = -2.5 * a * Log(Median-Intensity) - b * Mjk - c
                    a = 1 / Ka;
                    b = -Kb / Ka;
                    c = -Kc / Ka;

                    int starsExcludedThisTime = 0;

                    if (EXCLUDE_BAD_RESIDUALS)
                    {
                        List <int> indexesToRemove = new List <int>();
                        for (int i = 0; i < intencities.Count; i++)
                        {
                            double computed = a * -2.5 * Math.Log10(intencities[i]) + b * colours[i] + c;

                            double diff = Math.Abs(computed - magnitudes[i]);
                            if (itter < MAX_ITERR)
                            {
                                if (Math.Abs(diff) > maxResidual)
                                {
                                    indexesToRemove.Add(i);
                                }
                            }
                            else
                            {
                                residuals.Add(diff);
                            }
                        }


                        for (int i = indexesToRemove.Count - 1; i >= 0; i--)
                        {
                            int idxToRemove = indexesToRemove[i];
                            intencities.RemoveAt(idxToRemove);
                            magnitudes.RemoveAt(idxToRemove);
                            colours.RemoveAt(idxToRemove);
                            stars.RemoveAt(idxToRemove);
                            gaussians.RemoveAt(idxToRemove);
                            saturatedFlags.RemoveAt(idxToRemove);

                            excludedStars++;
                            starsExcludedThisTime++;
                        }
                    }

                    if (starsExcludedThisTime == 0)
                    {
                        break;
                    }
                }
            }
            catch (Exception ex)
            {
                Trace.WriteLine(ex.ToString());
            }

            return(new StarMagnitudeFit(
                       currentAstroImage,
                       bitPix,
                       intencities, magnitudes, colours, stars, gaussians, new List <double>(),
                       saturatedFlags, a, b, c, encodingGamma, reverseCameraResponse, excludedStars, filter, empericalFWHM,
                       photometryReductionMethod, photometryBackgroundMethod, psfQuadrature, psfFittingMethod, measurer, aperture));
        }
コード例 #28
0
 protected abstract bool ReadSolvedConstants(SafeMatrix bx, SafeMatrix by);
コード例 #29
0
 protected override void ReadSolvedReversedConstants(SafeMatrix bx, SafeMatrix by)
 {
 }
コード例 #30
0
        public ThreeStarAstrometry(AstroPlate image, Dictionary <ImagePixel, IStar> userStarIdentification, int tolerance)
        {
            if (userStarIdentification.Count != 3)
            {
                throw new InvalidOperationException();
            }

            Image     = image;
            UserStars = userStarIdentification.ToDictionary(kvp => kvp.Key, kvp => kvp.Value);

            double a0       = userStarIdentification.Values.Average(x => x.RADeg) * DEG_TO_RAD;
            double d0       = userStarIdentification.Values.Average(x => x.DEDeg) * DEG_TO_RAD;
            double corr     = double.MaxValue;
            int    attempts = 0;

            do
            {
                SafeMatrix AX = new SafeMatrix(3, 3);
                SafeMatrix X  = new SafeMatrix(3, 1);
                SafeMatrix AY = new SafeMatrix(3, 3);
                SafeMatrix Y  = new SafeMatrix(3, 1);

                int i = 0;
                foreach (var pixel in userStarIdentification.Keys)
                {
                    IStar  star = userStarIdentification[pixel];
                    double a    = star.RADeg * DEG_TO_RAD;
                    double d    = star.DEDeg * DEG_TO_RAD;

                    AX[i, 0] = pixel.XDouble;
                    AX[i, 1] = pixel.YDouble;
                    AX[i, 2] = 1;
                    AY[i, 0] = pixel.XDouble;
                    AY[i, 1] = pixel.YDouble;
                    AY[i, 2] = 1;

                    X[i, 0] = Math.Cos(d) * Math.Sin(a - a0) / (Math.Cos(d0) * Math.Cos(d) * Math.Cos(a - a0) + Math.Sin(d0) * Math.Sin(d));
                    Y[i, 0] = (Math.Cos(d0) * Math.Sin(d) - Math.Cos(d) * Math.Sin(d0) * Math.Cos(a - a0)) / (Math.Sin(d0) * Math.Sin(d) + Math.Cos(d0) * Math.Cos(d) * Math.Cos(a - a0));

                    i++;
                }

                SafeMatrix a_T    = AX.Transpose();
                SafeMatrix aa     = a_T * AX;
                SafeMatrix aa_inv = aa.Inverse();
                SafeMatrix bx     = (aa_inv * a_T) * X;

                m_A = bx[0, 0];
                m_B = bx[1, 0];
                m_C = bx[2, 0];

                a_T    = AY.Transpose();
                aa     = a_T * AY;
                aa_inv = aa.Inverse();
                bx     = (aa_inv * a_T) * Y;

                m_D = bx[0, 0];
                m_E = bx[1, 0];
                m_F = bx[2, 0];

                m_A0Rad = a0;
                m_D0Rad = d0;

                double ra_c, de_c;
                GetRADEFromImageCoords(Image.CenterXImage, Image.CenterYImage, out ra_c, out de_c);

                corr = AngleUtility.Elongation(ra_c, de_c, a0 * RAD_TO_DEG, d0 * RAD_TO_DEG) * 3600;
                a0   = ra_c * DEG_TO_RAD;
                d0   = de_c * DEG_TO_RAD;
                attempts++;
            }while (corr > tolerance && attempts < MAX_ATTEMPTS);

            Success = corr <= tolerance;
        }